Methods and systems for meeting rapidly fluctuating power demands using interruptible load and stable power production

ABSTRACT

An automated control method for meeting rapidly fluctuating power demands with stable power production is disclosed. The method includes determining a market value of a unit of electricity sold on the grid, a fuel cost required to produce the unit of electricity, and a market value of a processing task requiring the unit of electricity. The method also includes calculating which of the electricity, processing, or fuel is most valuable; shutting off a running process when the value of the electricity is highest or the value of the fuel is highest; and starting a pending process when the net market value of the processing task is highest. The method may also include reducing electricity generation at a power plant when the value of electricity is negative, or exercising a futures contract to supply electricity.

TECHNICAL FIELD

The present disclosure relates to the field of management of electricpower production, and, more particularly, methods and systems forrapidly responding to changes in electrical load demand by providingflexible electrical consumption providing economic benefit to the powergeneration facility.

BACKGROUND

Management of electric power production by traditional power plants hasbecome increasingly complex due to the rise in use of renewable energysources. Although electricity demand by consumers may be modeled basedon historical analysis of consumer activity, production of renewableenergy is difficult to predict. For example, the presence of a cloudover a solar power farm or wind gusting through a wind power farm maycause rapidly fluctuations in electric power production. Production maydecrease or increase by megawatts in a few minutes. Additionally, solarpower generation is highest during mid-day, while wind power generationmay be higher during day or night depending on location. Electric powerdemand, in contrast, sharply increases when workers return to theirhomes in the evening, just as renewable sources are decreasingproduction. Thus, renewable power generation may be variable and notcoincide with demand.

In order to meet this rapid demand increase coupled with rapid renewableproduction decrease that occurs in the evenings, operators oftraditional power plants, such as coal and gas turbine generators, mustquickly ramp up production using non-renewable sources. The startupphase of operating traditional generators is relatively more costly thanbaseline production, and often results in more pollution than ifoperators allowed the generator to run at a higher capacity utilizationrate throughout the day. Cutting production during daytime also reducesthe overall capacity utilization of the power plant, reducing economicincentives to build new plants and also extending the payback period andreturn on investment.

Alternatively, traditional power plants may operate at full capacitythroughout the day. However, to avoid causing frequency excursions ontransmission grids, plants must ensure that supply is equal to demand byoffloading surplus electricity. In some states, this is performed bycharging negative wholesale rates for electricity, thereby payingconsumers to use additional electricity. This practice reduces theprofitability of the generating plant. In some locations, productionfrom renewable sources is curtailed, requiring operators to reducegeneration far below capacity to avoid causing frequency excursions onthe grid, effectively throwing out power. This, too, reducesprofitability and incentives to build and to integrate renewable powergeneration sources.

Methods and systems that provide a profitable way to consume excesselectricity are desired. Further, electric power producers desiremethods and systems to quickly and responsively change consumption ofexcess electric power generated in order to meet consumer demand whilemaintaining cost-effective levels of operation, maintaining highcapacity utilization, reducing pollution, and avoiding or reducing theincreased cost and risk of equipment damage from rapid startup of powerplants.

SUMMARY

In one disclosed embodiment, a computer-implemented method forcontrolling power delivered to a grid is disclosed. The method of theembodiment utilizes an interruptible load that is operated in accordancewith the results of analysis of a number of parameters to determineefficient operation of both the power generation facility and the load.The method includes determining a market value of a unit of electricitysold on the grid, a production cost of the unit of electricity, a fuelcost required to produce the unit of electricity, a cost to sell fuel, amarket value of a processing task requiring the unit of electricity, anda cost of starting the processing. The method includes calculating, as anet market value of the unit of electricity, a first difference betweenthe market value of the unit of electricity and the production cost ofthe unit of electricity; calculating, as a net market value of theprocessing task, a second difference between the market value of theprocessing task and a sum of the production cost of the unit ofelectricity and the cost of starting the processing; and calculating, asa net market value of the fuel, a third difference between the fuel costand the cost to sell fuel; and calculating which of the net market valueof the unit of electricity, the net market value of the processing task,and the net market value of fuel is highest. The method further includesshutting off an interruptible load, corresponding to the processingtask, when the net market value of the unit of electricity is highest orthe net market value of the fuel is highest; and starting a pendingprocess corresponding to the processing task when the net market valueof the processing task is highest.

Embodiments of the method and system of the present disclosure aredescribed in relation to operation of power generation facilities. Themethods and systems disclosed also apply to power purchased from otherproducers or obtained from alternative sources of electric power,including without limitation the spot market or resellers. Thus, themethods and systems disclosed relating to power production, fuel cost,and related variables apply to comparable variables relating to powerobtained from other sources.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute partof this disclosure, together with the description, illustrate andexplain the principles of various exemplary embodiments of thedisclosure.

FIG. 1 is a graph illustrating representative values of total load, loadless solar and wind power contribution, and solar power production, on apower grid throughout a typical day. The values provided areillustrative and representative only and not intended to convey precisevalues.

FIG. 2 is a diagram illustrating the flow of fuel, electricity, andprocessing products, consistent with the present disclosure.

FIG. 3 is a flowchart of an example process for controlling powerdelivered to a grid, in accordance with embodiments of the presentdisclosure.

FIG. 4 is a flowchart of an example process for determining a processingtask having a highest value, in accordance with embodiments of thepresent disclosure.

FIG. 5 is a flowchart of an example process for prioritizing electricitydelivery, in accordance with embodiments of the present disclosure.

DETAILED DESCRIPTION

Reference will now be made in detail to the example embodimentsimplemented according to the present disclosure, the examples of whichare illustrated in the accompanying drawings. Wherever possible, thesame reference numbers will be used throughout the drawings to refer tothe same or like parts.

The present disclosure arises from the realization that electricalproduction costs including power plant startup operations, electrictransmission and distribution fees, and regulatory costs, includingcurtailment and demand charges, as well as introduction of renewableenergy sources, may impair or prevent optimized operation of powergenerating plants. The present disclosure proposes methods and systemsto optimize power plant generation by activating an interruptible load,such as processing resources, to consume excess electricity and producemarketable commodities, allowing power plants to operate moreeconomically at higher capacity utilization. An interruptible load maybe a load that may be shut off or reduced on demand without breaching anexpectation of reliable service. The present disclosure proposes methodsand systems to enable quicker response to changes in consumer electricaldemands by rapidly shutting off an interruptible load running theseprocesses while a power plant generates electricity at optimal output,freeing electricity for delivery to the grid for any consumption withoutcausing transient power plant operations. Further still, the presentdisclosure proposes methods and systems to precisely consume electricityso as to avoid regulatory penalties, poor capacity utilization, andtransmission costs. Additionally, in some embodiments, additional gridservices such as frequency control, voltage control, and voltage-amperereactive (VAR) controls may be serviced. For example, by altering thepower draw of an interruptible load, an operator may more easilymaintain a desired alternating current frequency delivered to customers.

The disclosed embodiments include computer-implemented methods andtangible non-transitory computer-readable media. Thecomputer-implemented methods can be executed, for example, by at leastone processor that receives instructions from a non-transitorycomputer-readable storage medium. Similarly, systems and devicesconsistent with the present disclosure can include at least oneprocessor and memory, and the memory can be a non-transitorycomputer-readable storage medium. As used herein, a non-transitorycomputer-readable storage medium refers to any type of physical memoryon which information or data readable by at least one processor can bestored.

Examples include random access memory (RAM), read-only memory (ROM),volatile memory, nonvolatile memory, hard drives, CD ROMs, DVDs, flashdrives, disks, and any other known physical storage medium. Singularterms, such as “memory” and “computer-readable storage medium,” canadditionally refer to multiple structures, such a plurality of memoriesor computer-readable storage mediums. As referred to herein, a “memory”can comprise any type of computer-readable storage medium unlessotherwise specified. A computer-readable storage medium can storeinstructions for execution by at least one processor, includinginstructions for causing the processor to perform steps or stagesconsistent with an embodiment herein. Additionally, one or morecomputer-readable storage mediums can be utilized in implementing acomputer-implemented method. The term “computer-readable storage medium”should be understood to include tangible items and exclude carrier wavesand transient signals.

The embodiments disclosed herein include systems that are operated bythe computer-implemented methods. Such systems may include, for example,facilities, factories, warehouses, hardware, power plants, renewableenergy farms, storage tanks, pipelines, and computer networks.Additionally, systems disclosed herein may include a memory andprocessor configured to perform operations including the disclosedmethods.

FIG. 1 illustrates power plant production levels needed to meet consumerelectrical demand over a 24-hour period. Power plant production isindicated by line 102, while actual load is indicated by line 104. Asillustrated, actual load increases throughout a day. However, renewableelectricity production, such as solar or wind, also contributeselectricity to meet the actual load. Thus, despite rising demandthroughout a day, generation by renewable energy sources, in particular,solar energy, causes reduced demand for conventional power duringmidday, illustrated as load and production difference 106. In thepresent example, solar power produces electricity during mid-day,between approximately 11:00 A.M. and 4:00 P.M. Beginning atapproximately 4:00 P.M., solar power production decreases with thesetting sun. At around this time, workers return home and beginenergy-intensive activities, such as bathing, cooking, cleaning, heatingand cooling, or charging an electric vehicle. The effect of a sharpdecrease in solar production, combined with an increase in consumerdemand, results in the steep increase in power plant production 108needed to meet consumer demand during the evening hours. As illustratedin FIG. 1, the demand may require an increase of power output of roughlythree thousand megawatts per hour for several hours.

In some situations, the equivalent of multiple power plants may need tobe activated to meet consumer demand. This added capacity may only beneeded for a few hours each day to meet the rising electrical demandbetween 4:00 P.M. and 8:00 P.M. The supplemental generating machinerythen remains idle for twenty hours each day, preventing plant operatorsfrom recouping baseline operating costs and capital investments of apower plant, such as inefficient startup operations, maintenance, andemployee costs, with more efficient operations outside of the startupperiod. Alternatively, power generating plants may operate at asuboptimal capacity utilization during the rest of the day in order tohave adequate capacity during peak hours, thus increasing the cost ofinstalling a plant, delaying plant payback, and reducing profitability.

Further, power plants are sometimes required to operate at a minimumemissions-compliant limit. When operating a reduced capacity, powerplants may not optimally combust fuel, or may not reach catalytictemperatures necessary to decompose pollutants. For nuclear powerplants, output may remain at a roughly constant level to increase safetyand reduce risks due to power transients. Therefore, due to regulations,power plants may be unable to reduce output below a threshold. In suchsituations, power companies may sell electricity to consumers at areduced or even negative rate, sometimes effectively paying customers toaccept excess power generation so that power plants may operate at amore efficient capacity utilization and remain above their respectiveminimum allowable operating levels. Although paying for users to consumeexcess electricity is undesirable, a power company may do so to meetregulatory limits and reduce maintenance or improvement costs due tostrain from excess power on the grid or strain from startup and shutdownoperations at a power plant.

Further, renewable generation plants may be forced to curtail productionto prevent grid frequency excursions or grid capacity constraints. Forexample, if a traditional power plant cannot decrease output to lessthan a certain proportion of total capacity due to safety requirements,minimum stable power production requirements, and regulations, a windfarm supplying the same grid may be required to stop electricityproduction entirely on a windy day so as to not overload a grid. Thiswastes power production opportunity and reduces profitability ofrenewable electricity generation, and inhibits investment in newtechnologies.

FIG. 2. illustrates an exemplary flow of fuel, electricity, andprocessing products. Fuel storage 202 provides fuel, such as coal, oil,natural gas, or nuclear fuel, to a power plant 204. Alternatively, aplant operator may decide to resell fuel on a commodities market 216.For instance, the value of the fuel on the market may be higher than thevalue of electricity produced by the fuel, such as during fuel shortagesor severe weather conditions in other locations. In some situations, thefuel may be transported, such as via pipeline or rail. Fuel may be soldfor future delivery without physically transporting the fuel to theinitial buyer, such that a plant in Chicago with a contract to takedelivery of natural gas in Mississippi may sell the right to the fuel toa powerplant in Biloxi, without the Chicago plant ever actually havingreceived physical delivery of the natural gas.

Fuel is provided to power plant 204, which, along with renewablegeneration sources 206, produces electricity. The electricity may beused to operate a processing plant 208 to produce a tangible commodity.For example, processing plant 208 may operate electrolyzers to producehydrogen and oxygen for sale on a commodities market for bottled gasses.Processing plant 208 may also be a pumped storage facility, operatingpumps to move water to a high retention facility to create electricityat a later time by flowing over a turbine, or by storing electricitydirectly in battery storage banks. The stored electricity may then besold on a market 216, for example, on the same grid to which the powergenerating plant supplies power.

Electricity from power plant 204 and renewable generation 206 alsosupplies computational resources 210. Computational resources 210 mayinclude, for example, supercomputer hardware configured to performparallel processing, train neural networks, or run computer models suchas protein folding, computational fluid dynamics, AI training protocols,particle physics transport, or any other appropriate computational task.Computational resources may also include application-specific integratedcircuits (ASICs) or graphical processing units (GPUs). ASICs and GPUsmay be configured to optimize cryptocurrency mining. For instance,computational resources 210 may host ASICs designed to mine acryptocurrency. In some embodiments, computational resources 210 mayinclude a plurality of hardware types configured for different purposes,such as mining a plurality of cryptocurrencies. Mined cryptocurrency maythen be traded for value, government-issued currency, or othercryptocurrencies on a commodities market 216, such as a cryptocurrencyexchange.

In some embodiments, processing plant 208 and computational resources210 may be connected to an electricity source in advance of grid 212.For example, processing plant 208 and computational resources 210 may beconnected between the output of power plant 204 and a step uptransformer or grid interconnect point that conditions power from powerplant 204 for delivery to consumers 214. In some embodiments, processingplant 208 and computational resources 210 may be constructed physicallyclose to a power generation source. Alternatively, processing plant 208and computational resources 210 may be constructed far from a powergeneration source, but still connected to a power generation sourcebetween an output and a step up transformer or grid interconnect point.Electricity consumed by the processing plant 208 and computationalresources 210 may avoid transmission and delivery fees incurred fordelivery of electricity downstream of a grid interconnect. Othertransaction costs may also be reduced, and demand fees or curtailmentrequirements may be avoided, because electricity is not transferred tothe grid 212.

Further, in some embodiments, processing plant 208 and computationalresources 210 may comprise systems that can be rapidly shut down andrapidly restarted with no or little damage to components or degradationof processing products. For example, if processing plant 208 includes anelectrolyzer, the electrolyzer may be turned off in seconds or minuteswithout damaging the electrolyzer. Further, all oxygen and hydrogen maybe secured by quickly closing valves, without the oxygen and hydrogendegrading during the time the power is switched off. Additionally, ifcomputational resources 210 include ASICs for bitcoin mining, a miningoperation may be cut off mid-process without loss of previously-minedbitcoin, which is recorded in the bitcoin blockchain or quickly sold forvalue. In some embodiments, processing plant 208 and computationalresources 210 may comprise an uninterruptible power supply whichprovides enough stored electricity to allow safe shutdown of a process,or to complete a task. For example, in the scenario of bitcoin mining,the likelihood of mining a block in the blockchain and collecting areward for doing so may increase with time spent working on a currentblock, such that as more time elapses, the block is more likely to bemined. Shutting down computational resources may therefore include adetermination of the likelihood of solving a block that is currentlybeing processed. Components in processing plant 208 and computationalresources 210 may be individually controlled, so that power consumptionrises or declines to match available excess power.

Additionally, grid 212 transmits power to consumers 214. Consumers maybe industrial, commercial, or residential. Different consumers may paydifferent rates per unit of electricity, such as a retail rate forresidences, and a wholesale rate for industry.

Thus, as illustrated in FIG. 2, an operator may control power productionand pre-grid electrical consumption to take advantage of commoditymarkets 216 for alternative products, while avoiding or minimizingtransmission and delivery charges and other penalties, and optimizingpower plant use. Further, an operator may reduce plant production andsell excess fuel to other consumers, increase processing plant 208 andcomputational resources 210 operation to absorb excess production, orreduce consumption by processing plant 208 and computational resources210 to meet consumer demand and prevent blackouts or take advantage ofhigher electrical prices during peak usage times. The operator may meetrapidly climbing consumer demand by quickly shutting down processing,freeing additional power for consumers 214 while avoiding costlyoperation transients in power plant 204 and enabling power generationplant to operate at a more optimal capacity utilization level.

FIG. 3 illustrates an exemplary process 300 for controlling powerdelivered to a grid, in accordance with embodiments of the presentdisclosure. Step 302 includes determining a plurality of values fordifferent commodities. For example, a product of a processing task maybe a commodity sold on an exchange, such as raw materials orcryptocurrencies, such that a purchaser is identified after the productis created, and the purchaser may acquire the commodity from any of aplurality of suppliers. The product may be non-perishable, such aspurified gasses, computational results stored in non-volatile memory, orstored electricity. Step 302 determines a market value of a unit ofelectricity sold on the grid, a production cost of the unit ofelectricity, a fuel cost required to produce the unit of electricity, acost to sell fuel, a market value of a processing task requiring theunit of electricity, and a cost of starting the processing. Step 302 mayinclude accessing websites, or other available sources, to determinemarket values of various items.

Step 304 includes calculating, as a net market value of the unit ofelectricity, a first difference between the market value of the unit ofelectricity and the production cost of the unit of electricity. Netmarket value may represent the profit gained by selling an item, such asthe difference between the sale price and the sum of production cost,employees, financing, equipment, amortization, and raw materials. Theproduction cost may include amortized maintenance and financing on anelectrical production facility (such as a power plant or solar farm).Production cost may also include wages for operators. In someembodiments, the market value of the unit of electricity sold includesat least one of energy production charges, demand charges, andtransmission and distribution charges. The unit of electricity sold maybe sold on the grid to consumers. Further, consumer type may varybetween wholesale and retail, and so an average market value may beused. Alternatively, models may be employed to determine the mostprofitable mix of wholesale and retail, or power may be sold at onlywholesale rates, or only retail rates. Production cost may also includetaxes and regulatory fees. In some embodiments, electricity may betraded between markets or producers. For example, an electricityproducer may trade electrical production required to meet renewableenergy requirements, or may also trade renewable energy credits.Additionally, an electricity producer may trade energy options orfutures. In these embodiments, transaction fees, such as dealer orexchange fees, may also be considered. For example, step 302 may includedetermining a purchase value of a futures contract for electricity, andstep 304 may include calculating, as a net market value of the unit ofelectricity, a difference between the market value of the unit ofelectricity and a proportion of the futures contract corresponding tothe unit of electricity.

Step 306 includes calculating, as a net market value of the processingtask, a second difference between the market value of the processingtask and a sum of the production cost of the unit of electricity and thecost of starting the processing. The cost of starting the process mayinclude electricity consumed while starting the process but not yetproducing a product, or expected equipment damage from the startup, suchas consumable switches and breakers, failure of electronic components,or cyclic fatigue of mechanical parts.

Additionally, in some embodiments, the energy cost associated with theprocessing task comprises energy production charges. In other words, thecost of electricity provided to the process may be lower than the costof electricity provided to consumers because the process may consumeelectricity upstream of transformers and interconnects, thereby avoidingdemand charges, transmission and distribution fees, taxes, and fees, andmay avoid electrical losses that would otherwise be incurred in thetransmission and distribution systems. Alternatively, the energy costassociated with the processing take may also include the same types ofcosts of providing electricity to consumers, but individual costs may bethe same or differ from those charged to consumers. Further, step 306may include calculating a difference between the market value of theprocessing task and the proportion of the futures contract correspondingto the unit of electricity.

Step 308 includes calculating, as a net market value of the fuel, athird difference between the fuel cost and the cost to sell fuel. Thefuel cost may vary depending on quantity of fuel sold to another party,for instance. The cost to sell fuel may also vary on the quantity, aswell as any brokerage fees increasing transaction cost.

Step 310 includes calculating which of the net market value of the unitof electricity, the net market value of the processing task, and the netmarket value of fuel is highest. Other factors affecting a net marketvalue, such as regulatory fees or taxes, may also be calculated andincorporated into the calculation of step 310. Step 310 may includecompare the net market value of the unit of electricity and the netmarket value of the processing task, disregarding the net market valueof fuel.

Step 312 includes shutting off a running process corresponding to theprocessing task when the net market value of the unit of electricity ishighest or the net market value of the fuel is highest. Step 312 mayshut off a portion of all running process, such that step 312 graduallyshuts down a running processes by selectively removing power tocomponents. Step 312 may sever power to all components. Step 312 mayfurther include a control mechanism, such as aproportional-integral-derivative (PID) controller, to calculate whichcomponents must be shut down to match reduction in power generation(such as when a cloud passes a solar farm or a steam turbine goesoffline), or match an increase in demand (such as during evening hours),or to match a combined reduction and increase.

Step 314 includes starting a pending process corresponding to theprocessing task when the net market value of the processing task ishighest. Step 314 may start a portion of total pending processes togradually increase consumption of excess power, or to match increases inexcess power consumption. Step 314 may incorporate a PID controller asdescribed for step 312. In this way, step 314 directs excess power awayfrom the grid into a more profitable use.

Step 312 and 314 may be performed in real-time, enabling responsive loadtransfer in conjunction with highly fluctuating production orconsumption. Step 312 and 314 may also be performed based on an averagedemand over a period of time to avoid excessive startup periods that areunproductive but nonetheless consume electricity and damage components.

Further, process 300 may include reducing electricity generation at apower plant and selling fuel when the net market value of the fuel ishighest. For instance, if an emergency in a first location damages fuelstores for power plants in the first location, power plants in a secondlocation not affected by the emergency may reduce production and sellfuel to power plants in the first location at a profit. Similarly, avariety of operating conditions, routine maintenance, or system orequipment failures, could result in a comparable difference between twolocations. In these situations, process 300 may initiate a saleautomatically, or may identify the opportunity to an operator forapproval. Additionally, the amount of fuel sold may be limited to ensurethe sufficient fuel exists to maintain electricity generation above aminimum emissions compliant limit.

Additionally, process 300 may include purchasing electricity at a lowercost than cost of producing the same electricity. This may occur, forexample, if one region has lower demand, and thus a lower electricityprice, than another region. Process 300 may include determining if themarket value of the unit of electricity sold on the grid is lower than atotal operating cost comprising the production cost of the unit ofelectricity, a startup cost to start power generation, and a shut-downcost to stop power generation; determining a cost of purchasingelectricity from a different electricity supplier; and purchasingelectricity from the different electricity supplier if the cost ofpurchasing electricity is less than the total operating cost.

In some scenarios, overproduction of electricity may cause curtailmentof production. For example, an operator of a wind power farm may need toreduce output by, for instance, altering wind turbine blade angle orbraking turbine movement. In this situation, although there is no excesspower, there is excess generating capacity which could be utilized toearn a profit and improve investment outcomes. Therefore, process 300may further include determining if curtailment policies require areduction in an amount of electricity delivered to the grid, forinstance, below an optimal production capacity.

Process 300 may include starting the pending process to consumeelectricity generated in excess of limits imposed by curtailmentpolicies. Alternatively, process 300 may start the pending process inconjunction with an increase optimization or increased production ofrenewable electrical production in order to prevent triggering ofcurtailment policies and any relates fees. In some embodiments, process300 may also determine an expected profit derived from consumingelectricity to avoid curtailment. That is, process 300 may also includedetermining a cost of curtailment fees, determining an expectedmaintenance cost incurred by operating during a curtailment period, andcalculating a net market value of curtailment processing as a differencebetween the net market value of the processing task and a sum of thecost of curtailment fees and expected maintenance cost. Process 300 mayalso include starting the pending process to consume electricitygenerated in excess of limits imposed by curtailment policies when thenet market value of curtailment processing exceeds a threshold.

In other alternatives, power generation may be stopped or shut down, andprocess 300 supplied electric power through back-feed of power from thegrid, or an alternative source of power. Further, the operator maycontract to have power delivered from an alternative source at any pointon the grid providing the ability to trade power as needed and themethods and system disclosed may be used in these situations as well.

FIG. 4 illustrates an exemplary process 400 for determining a processingtask having a highest value, in accordance with embodiments of thepresent disclosure. The processing task may include cryptocurrencymining. Step 402 of process 400 includes determining a reward forcompleting the cryptocurrency mining task. For instance, if the processincludes bitcoin mining, the reward may be newly minted bitcoin,provided upon determining a nonce value for a block. Step 404 includesaccessing a cryptocurrency exchange to determine an exchange rate of thereward to a currency. The currency may be government-backed, such asdollars or euros, or a different cryptocurrency, or another form ofvaluable consideration.

Step 406 includes determining an expected fraction of the reward bymultiplying the reward and a probability of obtaining the reward. Forexample, in the case of bitcoin mining, a bitcoin block is mined and areward issued approximately every ten minutes. If an ASIC starts miningfive minutes after the previous block was mined, the likelihood of theASIC mining the next block is halved. Additionally, the likelihood ofthe ASIC mining the next block corresponds to a fraction of the ASIChashing rate and the total hashing capability of the bitcoin network. Insome embodiments, processing power may be joined to other processors ina pool which distributes fractions of the reward to members of the poolaccording to the fraction of total processing provided to the pool,allowing a consistent, but lower, reward. In this case, step 406 mayfurther determine a reward by subtracting any pool fees.

The time to mine a block varies, and may be more than an hour, althoughthe bitcoin network targets a new block being mined approximately everyten minutes. In some embodiments, the amount of time elapsed past thetarget time, or an amount of time elapsed since a previous block wasmined, may be used to determine the likelihood that a new block will bemined in a subsequent time interval. Block mining times may be arrangedin a distribution of past mining intervals and modeled as a Poissondistribution or an exponential distribution, having a mean, forinstance, of 10 minutes. With this information, the likelihood of ablock being mined in the next minute given that the last block was minedtwenty minutes ago may be calculated. This likelihood may be included ina determination of shutting down or continuing processing, for instance,by being incorporated into an expected profit by multiplying the rewardvalue by the likelihood.

Step 408 includes converting the expected fraction of the reward to thecurrency based on the exchange rate. Further, step 410 includesestimating an energy cost associated with the processing task. Forinstance, step 410 may estimate cost based on the amount of timeremaining until a reward is issued. Step 412 includes setting the marketvalue of the processing task to be the difference between the convertedreward fraction and the estimated cost.

Further, the processing task may include a computational task requiredby, for instance, researchers. The processing task may include acomputational model or neural network training operation configured tooperate intermittently at least by saving progress while the processingtask is operating. For example, if a researcher is training a neuralnetwork, weights for each neuron in the neural network may be stored ina non-volatile memory so that if a power supply is severed, training mayquickly resume with no lost progress once power resumes. In this way, aresearcher who does not require uninterrupted processing may benefitfrom cost savings available due to cheaper electricity, while the powergenerator may benefit from greater capacity use. For example, analgorithm may receive an input that an operator wants to shut downprocessing, and the algorithm may suggest an approval or disapproval inaccordance with financial impacts of shutting down and the time frame.

In some embodiments, process 400 may further include determining amarket value for each of a plurality of processing tasks. For example,process 400 may determine the market value of a plurality ofcryptocurrencies. Process 400 may also include setting the pendingprocess to be the processing task among the plurality of processingtasks having a highest market value. For example, process 400 maycalculate the expected amount of time and dollar value of the reward tomine bitcoin and Ethereum, as well as respective electricity costs andany incurred fees, such as pool fees or transaction fees. Process 400may then designate the most valuable cryptocurrency as the pendingprocess that will start when its value is highest. Further, process 400may start the pending process by starting hardware optimized to performthe pending process, and shut off hardware optimized to perform tasksother than the pending process. For example, if etherium is the highestvalue, process 300 may start GPUs designed to mine Ethereum and shutdown ASICs for bitcoin mining, or let them remain idle if they are notoperating.

FIG. 5 is a flowchart of an exemplary process 500 for prioritizingelectricity delivery, in accordance with embodiments of the presentdisclosure. At times, selling electricity to the grid may not presentthe highest value. Yet, supplying increased electricity to consumers attime of increased demand may be necessary to prevent blackouts orbrownouts. Thus, in some embodiments, electricity may be provided toconsumers even though selling fuel or using the electricity to minecryptocurrency or produce a commodity is more valuable.

Process 500 may be used to ensure that essential services, such ashospitals, high priority services, such as commercial facilities,industry, and homes, and discretionary services, such as energy storage,receive electricity according to priority. This may, for example,decrease the risk of blackouts or brownouts. Further, by controlling adiscretionary but profitable load using process 500, an electricityprovider may ensure sufficient capacity exists to meet consumer needs byoperating at electrical production at full capacity and using excessproduction to recoup investment and maintenance costs and avoiding lostproductivity.

Step 502 includes categorizing electricity consumers as discretionary ormandatory. For example, hospitals, nursing homes, air traffic control,water supply, and transportation may be identified as mandatoryconsumers, while movie theaters, malls, and warehouses may be identifiedas discretionary. Mandatory loads may also have a backup generator orelectricity storage for added redundancy. Step 504 includes determininga mandatory electricity demand as a total demand of consumerscategorized as mandatory. Step 506 includes calculating a reserve supplycapacity as a product of a safety margin and the mandatory electricitydemand. For example, the method and system may maintain a thresholdproduction capacity or preset margin above a threshold productioncapacity so that spikes in usage will not result in a power outage forcertain functions.

Step 508 includes determining a current electricity supply of the grid,and step 510 includes determining a current electricity demand of thegrid. In some embodiments, supply and demand of a portion of a grid maybe analyzed. Process 500 thus monitors electricity demand of consumersusing the grid.

Step 512 includes starting cryptocurrency mining hardware when thecurrent electricity supply exceeds the sum of the current electricitydemand and the reserve supply capacity. In other words, if consumerdemand and reserve supply are met, and supply equals demand, step 512may start cryptocurrency hardware to utilize surplus capacity. In someembodiments, step 512 may also increase electrical production if surpluscapacity exists, allowing more cryptocurrency mining hardware to start.

If processing plant 208 or computational resources 210 are in operation,the running process may be shut off when the sum of electricity demandand electricity use by the running process exceeds electricity supply.Thus, step 514 includes shutting down cryptocurrency mining hardwarewhen the current electricity supply is less than the sum of the currentelectricity demand and the reserve supply capacity. Step 514 may alsoincrease electrical production, or may maintain electrical product andcreate additional supply by reducing the load caused by cryptocurrencymining hardware.

In other words, process 500 may include operating a power plant at aconstant production level and shutting off a running process or startinga pending process such that electricity delivered to the grid matchesconsumer electricity demand. In this way, process 500 may “throttle”delivery to the grid by controlling pre-grid consumption rather than bychanging power plant operation, enabling the power generation facilityto operate at a more favorable capacity utilization level.

In the preceding disclosure, various example embodiments have beendescribed with reference to the accompanying drawings. It will, however,be understood by persons skilled in the art that various modificationsand changes may be made thereto, and additional embodiments may beimplemented, without departing from the broader scope of the disclosureas set forth in the claims that follow. The disclosure and drawings areaccordingly to be regarded as illustrative rather than restrictive. Forexample, the present disclosure illustrates various methods of managingelectric power production. The methods and systems disclosed also applyto power that is purchased from other producers or from alternativesources of electric power, including without limitation the spot marketor resellers. Thus, the methods and systems disclosed relating to powerproduction, fuel cost, and related variables should be understood toapply as well to comparable variables relating to power obtained fromother sources.

Therefore, it is intended that the disclosed embodiments and examples beconsidered as examples only, with a true scope of the present disclosurebeing indicated by the following claims and their equivalents.

What is claimed is:
 1. A computer-implemented method for controllingpower delivered to a grid, comprising: determining a market value of aunit of electricity sold on the grid, a production cost of the unit ofelectricity, a fuel cost required to produce the unit of electricity, acost to sell fuel, a market value of a processing task requiring theunit of electricity, and a cost of starting the processing; calculating,as a net market value of the unit of electricity, a first differencebetween the market value of the unit of electricity and the productioncost of the unit of electricity; calculating, as a net market value ofthe processing task, a second difference between the market value of theprocessing task and a sum of the production cost of the unit ofelectricity and the cost of starting the processing; calculating, as anet market value of the fuel, a third difference between the fuel costand the cost to sell fuel; calculating which of the net market value ofthe unit of electricity, the net market value of the processing task,and the net market value of fuel is highest; shutting off a runningprocess corresponding to the processing task when the net market valueof the unit of electricity is highest or the net market value of thefuel is highest; and starting a pending process corresponding to theprocessing task when the net market value of the processing task ishighest.
 2. The method of claim 1, wherein: the processing taskcomprises cryptocurrency mining; determining the market value of theprocessing task comprises: determining a reward for completing acryptocurrency mining task; accessing a cryptocurrency exchange todetermine an exchange rate of the reward to a currency; determining anexpected fraction of the reward by multiplying the reward and aprobability of obtaining the reward; converting the expected fraction ofthe reward to the currency based on the exchange rate; estimating anenergy cost associated with the processing task; and setting the marketvalue of the processing task to be the difference between the convertedreward fraction and the estimated energy cost.
 3. The method of claim 2,wherein: the market value of the unit of electricity comprises at leastone of energy production charges, demand charges, and transmission anddistribution charges; and the energy cost associated with the processingtask comprises energy production charges.
 4. The method of claim 2,wherein the probability of obtaining the reward comprises a likelihoodthat a block of a blockchain will be mined within a time interval, thelikelihood being based on a distribution of past mining intervals, atarget mining time, and an amount of time elapsed since a previous blockwas mined.
 5. The method of claim 1, further comprising: determining amarket value for each of a plurality of processing tasks; and settingthe pending process to be the processing task among the plurality ofprocessing tasks having a highest market value; and starting the pendingprocess comprises: starting hardware optimized to perform the pendingprocess; and shutting off hardware optimized to perform tasks other thanthe pending process.
 6. The method of claim 1, wherein: shutting off therunning process comprises shutting off a portion of all runningprocesses; and starting the pending process comprises starting a portionof total pending processes.
 7. The method of claim 1, furthercomprising: reducing electricity generation at a power plant and sellingfuel when the net market value of the fuel is highest.
 8. The method ofclaim 1, further comprising: determining if the market value of the unitof electricity sold on the grid is lower than a total operating costcomprising the production cost of the unit of electricity, a startupcost to start power generation, and a shut down cost to stop powergeneration; determining a cost of purchasing electricity from analternative electric power supplier; and purchasing electricity from thedifferent electricity supplier if the cost of purchasing electricity isless than the total operating cost.
 9. The method of claim 8, whereinelectricity generation is maintained above a minimum emissions compliantlimit.
 10. The method of claim 1, further comprising: determining ifcurtailment policies require a reduction in an amount of electricitydelivered to the grid; and starting the pending process to consumeelectricity generated in excess of limits imposed by curtailmentpolicies.
 11. The method of claim 1, further comprising: monitoringelectricity demand of consumers using the grid; and shutting off therunning process when a second sum of electricity demand and electricityuse by the running process exceeds electricity supply.
 12. The method ofclaim 11, further comprising: operating a power plant at a substantiallyconstant production level; and shutting off the running process orstarting the pending process such that electricity delivered to the gridmatches consumer electricity demand.
 13. The method of claim 1, wherein:the processing task comprises a computational model or neural networktraining operation configured to operate intermittently at least bysaving progress while the processing task is operating.
 14. The methodof claim 1, wherein: the processing task comprises storing energy in atleast one of a battery storage bank or a pumped storage facility. 15.The method of claim 1, wherein a product of the processing task is acommodity sold on an exchange, such that a purchaser is identified afterthe product is created and the purchaser may acquire the commodity fromany of a plurality of suppliers.
 16. A computer-implemented method forcontrolling power delivered to a grid, comprising: categorizingelectricity consumers as discretionary or mandatory; determining amandatory electricity demand as a total demand of consumers categorizedas mandatory; calculating a reserve supply capacity as a product of asafety margin and the mandatory electricity demand; determining acurrent electricity supply of the grid; determining a currentelectricity demand of the grid; starting cryptocurrency mining hardwarewhen the current electricity supply exceeds the sum of the currentelectricity demand and the reserve supply capacity; and shutting downcryptocurrency mining hardware when the current electricity supply isless than the sum of the current electricity demand and the reservesupply capacity.
 17. The method of claim 16, wherein: the processingtask comprises cryptocurrency mining; determining the market value ofthe processing task comprises: determining a reward for completing acryptocurrency mining task; accessing a cryptocurrency exchange todetermine an exchange rate of the reward to a currency; determining anexpected fraction of the reward by multiplying the reward and aprobability of obtaining the reward; converting the expected fraction ofthe reward to the currency based on the exchange rate; estimating anenergy cost associated with the processing task; and setting the marketvalue of the processing task to be the difference between the convertedreward fraction and the estimated energy cost.
 18. Acomputer-implemented method for controlling power delivered to a grid,comprising: determining a market value of a unit of electricity sold onthe grid, a purchase value of a futures contract for electricity, amarket value of a processing task requiring the unit of electricity, anda cost of starting the processing; calculating, as a net market value ofthe unit of electricity, a first difference between the market value ofthe unit of electricity and a proportion of the futures contractcorresponding to the unit of electricity; calculating, as a net marketvalue of the processing task, a second difference between the marketvalue of the processing task and the proportion of the futures contractcorresponding to the unit of electricity; calculating which of the netmarket value of the unit of electricity and the net market value of theprocessing task is highest; shutting off a running process correspondingto the processing task when the net market value of the unit ofelectricity is highest; and starting a pending process corresponding tothe processing task when the net market value of the processing task ishighest.
 19. The method of claim 18, wherein: the processing taskcomprises cryptocurrency mining; determining the market value of theprocessing task comprises: determining a reward for completing acryptocurrency mining task; accessing a cryptocurrency exchange todetermine an exchange rate of the reward to a currency; determining anexpected fraction of the reward by multiplying the reward and aprobability of obtaining the reward; converting the expected fraction ofthe reward to the currency based on the exchange rate; estimating anenergy cost associated with the processing task; and setting the marketvalue of the processing task to be the difference between the convertedreward fraction and the estimated energy cost.
 20. The method of claim19, wherein the probability of obtaining the reward comprises alikelihood that a block of a blockchain will be mined within a timeinterval, the likelihood being based on a distribution of past miningintervals, a target mining time, and an amount of time elapsed since aprevious block was mined.